Intern, Data Engineering Job at EDP (Singapore)

Job Description

We are looking for a curious, technically strong undergraduate intern to join our E&C team and help us unlock the value of our Construction Management Tool (CMT) data. This is a hands-on, exploratory role at the intersection of data engineering, AI, and real-world industrial operations. If you are looking for an internship where you will spend your time on toy datasets and predefined exercises — this is not it. You will work with production data from live renewable energy projects, develop a deep understanding of how that data is structured, and — critically — define how AI can be applied to it. The use cases you identify and the groundwork you lay will directly feed into the AI initiatives this team pursues next. This is early-stage, high-ownership work. The right candidate will be energised by ambiguity, driven by curiosity, and excited by the idea of shaping something from the ground up.

Job Responsibility

Data architecture mapping — understand the CMT data model end-to-end: tables, relationships, data flows, and how project information is captured across the solar, wind, and BESS delivery lifecycle
Data catalogue development — document data assets in a structured, accessible catalogue: field definitions, data types, quality observations, and coverage gaps
Exploratory data analysis — query and profile the data to surface patterns, anomalies, and signals relevant to project delivery performance
AI use case identification — drawing on your understanding of the CMT data and the broader E&C workflow, you will identify and document potential AI/ML applications across the business: predictive analytics, anomaly detection, scheduling optimisation, procurement insights, process automation, and beyond. For each candidate use case, you will assess feasibility, data readiness, and potential business value — building a tangible AI opportunity map for the team
AI/ML groundwork — assess the data landscape for ML readiness
identify what data preparation, enrichment, or pipeline work would be required to bring priority use cases to life
Collaboration — work closely with E&C project managers, planners, and engineers to contextualise data with domain knowledge and pressure-test your ideas against operational reality

Requirements

Penultimate or final year undergraduate student in Data Science, Artificial Intelligence, Machine Learning, or a related quantitative discipline
Proficiency in SQL
Python for data analysis (pandas, numpy, matplotlib/seaborn or equivalent)
Familiarity with data engineering concepts: schemas, ETL pipelines, data lineage
Exposure to ML workflows — feature engineering, model evaluation, supervised/unsupervised methods
Experience with cloud data platforms or datalake environments is a plus
Intellectually curious
Comfortable with unstructured problems
able to scope your own work
Clear communicator
Detail-oriented when it matters (data quality, documentation)
Prior exposure to energy, infrastructure, or construction project data
Experience with data cataloguing tools (e.g. DataHub, Atlan, or even structured Notion/Confluence documentation)
Familiarity with BI tools (Power BI, Tableau) for exploratory visualisation

Nice to have

Experience with cloud data platforms or datalake environments
Prior exposure to energy, infrastructure, or construction project data
Experience with data cataloguing tools (e.g. DataHub, Atlan, or even structured Notion/Confluence documentation)
Familiarity with BI tools (Power BI, Tableau) for exploratory visualisation

What we offer

Professional experience in a leading global company in the renewables industry with flexible work conditions
Recognition through remuneration compatible with the role and other additional benefits
Opportunities for personal and professional development, e.g. cross-cutting projects, mobilities and volunteering

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Intern, Data Engineering

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